It has felt like storms are getting worse. Does the data support that feeling?
Author
Earth & Space Science
HS-ESS2-5HS-ESS2-8HS-ESS3-5Unit Duration: 18β30 days
22 Anchor Phenomenon
22.1 π It Has Felt Like Storms Are Getting Worse
Does the data support that feeling, and will it continue?
In recent years, powerful storms have battered communities across the United States. From deadly blizzards burying the Northeast under feet of snow to Category 5 hurricanes devastating coastal cities, it feels like extreme weather is getting worse. But science doesnβt run on feelingsβit runs on evidence.
In this unit, you will investigate whether storms really are becoming more frequent and intense, and use climate models to argue what the future may hold for your community.
23 Unit Driving Question
23.0.1 Will there be more frequent and more intense severe storms in the future?
This question will guide your work across all four lesson sequences in this unit. By the end, you will construct an evidence-based argument about how climate change may alter storm patterns in your region.
24 What Makes This Unit Different?
This unit builds directly on Unit 4: Climate Change, where you analyzed data about Earthβs changing climate. Now youβll apply that understanding to a question that hits close to home: how might climate change affect the storms that impact your city?
Instead of memorizing weather vocabulary, youβll:
π¬ Build models of how storms form
π Analyze real data on storm frequency and intensity
πΊοΈ Read weather maps like a meteorologist
π¬ Construct arguments about future climate impacts
25 Unit Storyline Overview
25.0.1 Four Lesson Sequences β One Big Question
Each 5E sequence below addresses part of the unit driving question. Together they build toward a final performance task where you argue how storms in your region may change in the future.
Investigative Phenomenon: Winter storm Jonas produced strong enough winds and enough snow to cause significant disruptions to society, damage to property, and harm to human life.
Key Questions: How do severe winter storms form? What causes wind and precipitation?
HS-ESS2-8
25.0.3 πΊοΈ Sequence 2: The Paths of Severe Storms (6β11 days)
Investigative Phenomenon: Maps from 2018β2020 show that blizzards and hurricanes exhibit clear patterns in where they start and the direction in which they travel.
Key Questions: Why do severe storms follow the paths they do? How might those paths shift with warming?
HS-ESS2-8
25.0.4 π Sequence 3: Hurricanes (5β6 days)
Investigative Phenomenon: In 2005, hurricanes occurred in the North Atlantic Ocean between June and November 30, just like 2018 and 2020.
Key Questions: How do hurricanes form? Why do they occur only at certain times of year?
HS-ESS2-5
25.0.5 π’ Unit Closing: Constructing Your Argument (0β2 days)
Performance Task: Construct an oral argument from data analysis explaining how storms may change in the future in your region.
HS-ESS3-5
26 Storms by the Numbers
Letβs look at some real data to start building your intuition about whether storms are changing.
Code
Plot =require("@observablehq/plot")// Named Atlantic hurricanes per yearhurricaneData = [ {year:1980,count:11}, {year:1985,count:11}, {year:1990,count:14}, {year:1995,count:19}, {year:1996,count:13}, {year:1997,count:8}, {year:1998,count:14}, {year:1999,count:12}, {year:2000,count:15}, {year:2001,count:15}, {year:2002,count:12}, {year:2003,count:16}, {year:2004,count:15}, {year:2005,count:28}, {year:2006,count:10}, {year:2007,count:15}, {year:2008,count:16}, {year:2009,count:9}, {year:2010,count:19}, {year:2011,count:19}, {year:2012,count:19}, {year:2013,count:14}, {year:2014,count:8}, {year:2015,count:11}, {year:2016,count:15}, {year:2017,count:17}, {year:2018,count:15}, {year:2019,count:18}, {year:2020,count:30}, {year:2021,count:21}, {year:2022,count:14}, {year:2023,count:20}, {year:2024,count:18}]Plot.plot({title:"Named Atlantic Storms per Year (1980β2024)",subtitle:"Has there been a trend?",width:750,height:400,x: {label:"Year"},y: {label:"Number of Named Storms",domain: [0,35]},marks: [ Plot.barY(hurricaneData, {x:"year",y:"count",fill: d => d.count>=20?"#e74c3c": d.count>=15?"#f39c12":"#3498db"}), Plot.ruleY([14], {stroke:"#999",strokeDasharray:"5,5"}), Plot.text([{x:1985,y:15.5}], {x:"x",y:"y",text: d =>"1991β2020 average: ~14",fill:"#999",fontSize:11}), Plot.linearRegressionY(hurricaneData, {x:"year",y:"count",stroke:"#e74c3c",strokeWidth:2,strokeDasharray:"8,4"}) ]})
26.0.1 π€ Initial Questions β What Do You Notice? What Do You Wonder?
Take a moment to study the graph above. In your notebook, write down:
What patterns do you notice in the number of named storms over time?
What questions do you have about why the numbers vary so much from year to year?
Do you think storms are getting worse? What evidence from this graph would you use to support your claim?
What additional data would you want to see to answer the unit driving question?
27 Connecting to Unit 4
In Unit 4, you learned that:
Human activities have increased atmospheric COβ from 280 ppm to over 420 ppm
This enhanced greenhouse effect is raising global temperatures
Positive feedback loops (ice-albedo, water vapor, permafrost) amplify warming
Climate models project continued warming throughout the 21st century
27.0.1 π Making Connections
Now consider: How might a warmer atmosphere and warmer oceans change storm behavior?
Write a brief hypothesis in your notebook. Weβll revisit it at the end of the unit to see how your thinking has evolved.
28 What Youβll Figure Out
By the end of this unit, you will be able to:
Sequence
You Will Figure Outβ¦
Blizzards
Wind is caused by uneven heating β pressure differences. Cold and warm air masses collide to produce precipitation. Mid-latitude cyclones become blizzards under certain conditions.
Storm Paths
Global winds driven by uneven solar heating drive storm trajectories. Wind patterns may shift as temperatures rise.
Hurricanes
Hurricanes get energy from warm ocean water. Ocean temperature seasonality explains hurricane season.
Closing
You can construct an evidence-based argument about future storm changes in your region.
29 Getting Started
In the next chapter, weβll dive into our first investigative phenomenon: Winter Storm Jonas and the science behind blizzard formation. Get ready to think like a meteorologist! π¨οΈ
---title: "Unit 5: More Hurricanes & Blizzards in NYC? β Unit Opening"subtitle: "It has felt like storms are getting worse. Does the data support that feeling?"author: "Earth & Space Science"format: html: toc: true toc-depth: 3 number-sections: true theme: cosmo code-fold: true self-contained: trueexecute: echo: true warning: false---```{=html}<style>@import url('https://fonts.googleapis.com/css2?family=Space+Grotesk:wght@700&family=Inter:wght@400;600;800&display=swap');.anchor-box { background: linear-gradient(135deg, #1a1a2e 0%, #16213e 50%, #0f3460 100%); color: white; padding: 30px; border-radius: 15px; margin: 25px 0; box-shadow: 0 10px 30px rgba(15, 52, 96, 0.5); animation: slideIn 0.8s ease-out;}.driving-question { font-family: 'Space Grotesk', sans-serif; font-size: 1.6em; background: linear-gradient(90deg, #e94560, #ff6b6b); -webkit-background-clip: text; -webkit-text-fill-color: transparent; background-clip: text; margin: 15px 0;}.unit-overview { background: linear-gradient(135deg, #0f3460 0%, #533483 100%); color: white; padding: 25px; border-radius: 15px; margin: 20px 0;}.sequence-card { background: white; border-radius: 12px; padding: 20px; margin: 15px 0; border-left: 5px solid; box-shadow: 0 4px 15px rgba(0,0,0,0.08); transition: transform 0.2s ease;}.sequence-card:hover { transform: translateY(-2px); }.sequence-card.blizzard { border-color: #3498db; }.sequence-card.paths { border-color: #27ae60; }.sequence-card.hurricane { border-color: #e74c3c; }.pe-badge { display: inline-block; background: linear-gradient(135deg, #e94560, #c62828); color: white; padding: 5px 12px; border-radius: 20px; font-size: 12px; font-weight: 700; margin: 3px;}.phenomenon-box { background: linear-gradient(135deg, #f093fb 0%, #f5576c 100%); color: white; padding: 25px; border-radius: 15px; margin: 20px 0; box-shadow: 0 8px 25px rgba(245, 87, 108, 0.3);}.student-questions { background: #fff3e0; border-left: 5px solid #ff9800; padding: 20px; margin: 15px 0; border-radius: 0 10px 10px 0;}.check-understanding { background-color: #e8eaf6; border-left: 5px solid #3f51b5; padding: 15px; margin: 15px 0; border-radius: 0 10px 10px 0;}@keyframes slideIn { from { opacity: 0; transform: translateY(20px); } to { opacity: 1; transform: translateY(0); }}@keyframes pulse { 0%, 100% { transform: scale(1); } 50% { transform: scale(1.02); }}</style>```<span class="pe-badge">HS-ESS2-5</span> <span class="pe-badge">HS-ESS2-8</span> <span class="pe-badge">HS-ESS3-5</span> <span class="pe-badge">Unit Duration: 18β30 days</span># Anchor Phenomenon::: {.anchor-box}## π It Has Felt Like Storms Are Getting Worse[**Does the data support that feeling, and will it continue?**]{.driving-question}In recent years, powerful storms have battered communities across the United States. From deadly blizzards burying the Northeast under feet of snow to Category 5 hurricanes devastating coastal cities, it *feels* like extreme weather is getting worse. But science doesn't run on feelingsβit runs on **evidence**.In this unit, you will investigate whether storms really are becoming more frequent and intense, and use climate models to argue what the future may hold for your community.:::# Unit Driving Question::: {.phenomenon-box}### Will there be more frequent and more intense severe storms in the future?This question will guide your work across all four lesson sequences in this unit. By the end, you will construct an evidence-based argument about how climate change may alter storm patterns in your region.:::# What Makes This Unit Different?This unit builds directly on **Unit 4: Climate Change**, where you analyzed data about Earth's changing climate. Now you'll apply that understanding to a question that hits close to home: **how might climate change affect the storms that impact your city?**Instead of memorizing weather vocabulary, you'll:- π¬ **Build models** of how storms form- π **Analyze real data** on storm frequency and intensity- πΊοΈ **Read weather maps** like a meteorologist- π¬ **Construct arguments** about future climate impacts# Unit Storyline Overview::: {.unit-overview}### Four Lesson Sequences β One Big QuestionEach 5E sequence below addresses part of the unit driving question. Together they build toward a final performance task where you argue how storms in your region may change in the future.:::::: {.sequence-card .blizzard}### π¨οΈ Sequence 1: Blizzards (7β13 days)**Investigative Phenomenon:** Winter storm Jonas produced strong enough winds and enough snow to cause significant disruptions to society, damage to property, and harm to human life.**Key Questions:** How do severe winter storms form? What causes wind and precipitation?<span class="pe-badge">HS-ESS2-8</span>:::::: {.sequence-card .paths}### πΊοΈ Sequence 2: The Paths of Severe Storms (6β11 days)**Investigative Phenomenon:** Maps from 2018β2020 show that blizzards and hurricanes exhibit clear patterns in where they start and the direction in which they travel.**Key Questions:** Why do severe storms follow the paths they do? How might those paths shift with warming?<span class="pe-badge">HS-ESS2-8</span>:::::: {.sequence-card .hurricane}### π Sequence 3: Hurricanes (5β6 days)**Investigative Phenomenon:** In 2005, hurricanes occurred in the North Atlantic Ocean between June and November 30, just like 2018 and 2020.**Key Questions:** How do hurricanes form? Why do they occur only at certain times of year?<span class="pe-badge">HS-ESS2-5</span>:::::: {.sequence-card}### π’ Unit Closing: Constructing Your Argument (0β2 days)**Performance Task:** Construct an oral argument from data analysis explaining how storms may change in the future in your region.<span class="pe-badge">HS-ESS3-5</span>:::# Storms by the NumbersLet's look at some real data to start building your intuition about whether storms are changing.```{ojs}//| echo: falsePlot = require("@observablehq/plot")// Named Atlantic hurricanes per yearhurricaneData = [ {year: 1980, count: 11}, {year: 1985, count: 11}, {year: 1990, count: 14}, {year: 1995, count: 19}, {year: 1996, count: 13}, {year: 1997, count: 8}, {year: 1998, count: 14}, {year: 1999, count: 12}, {year: 2000, count: 15}, {year: 2001, count: 15}, {year: 2002, count: 12}, {year: 2003, count: 16}, {year: 2004, count: 15}, {year: 2005, count: 28}, {year: 2006, count: 10}, {year: 2007, count: 15}, {year: 2008, count: 16}, {year: 2009, count: 9}, {year: 2010, count: 19}, {year: 2011, count: 19}, {year: 2012, count: 19}, {year: 2013, count: 14}, {year: 2014, count: 8}, {year: 2015, count: 11}, {year: 2016, count: 15}, {year: 2017, count: 17}, {year: 2018, count: 15}, {year: 2019, count: 18}, {year: 2020, count: 30}, {year: 2021, count: 21}, {year: 2022, count: 14}, {year: 2023, count: 20}, {year: 2024, count: 18}]Plot.plot({ title: "Named Atlantic Storms per Year (1980β2024)", subtitle: "Has there been a trend?", width: 750, height: 400, x: {label: "Year"}, y: {label: "Number of Named Storms", domain: [0, 35]}, marks: [ Plot.barY(hurricaneData, {x: "year", y: "count", fill: d => d.count >= 20 ? "#e74c3c" : d.count >= 15 ? "#f39c12" : "#3498db"}), Plot.ruleY([14], {stroke: "#999", strokeDasharray: "5,5"}), Plot.text([{x: 1985, y: 15.5}], {x: "x", y: "y", text: d => "1991β2020 average: ~14", fill: "#999", fontSize: 11}), Plot.linearRegressionY(hurricaneData, {x: "year", y: "count", stroke: "#e74c3c", strokeWidth: 2, strokeDasharray: "8,4"}) ]})```::: {.student-questions}### π€ Initial Questions β What Do You Notice? What Do You Wonder?Take a moment to study the graph above. In your notebook, write down:1. **What patterns do you notice** in the number of named storms over time?2. **What questions do you have** about why the numbers vary so much from year to year?3. **Do you think storms are getting worse?** What evidence from this graph would you use to support your claim?4. **What additional data** would you want to see to answer the unit driving question?:::# Connecting to Unit 4In Unit 4, you learned that:- Human activities have increased atmospheric COβ from 280 ppm to over 420 ppm- This enhanced greenhouse effect is raising global temperatures- Positive feedback loops (ice-albedo, water vapor, permafrost) amplify warming- Climate models project continued warming throughout the 21st century::: {.check-understanding}### π Making ConnectionsNow consider: **How might a warmer atmosphere and warmer oceans change storm behavior?**Write a brief hypothesis in your notebook. We'll revisit it at the end of the unit to see how your thinking has evolved.:::# What You'll Figure OutBy the end of this unit, you will be able to:| Sequence | You Will Figure Out... ||----------|----------------------|| **Blizzards** | Wind is caused by uneven heating β pressure differences. Cold and warm air masses collide to produce precipitation. Mid-latitude cyclones become blizzards under certain conditions. || **Storm Paths** | Global winds driven by uneven solar heating drive storm trajectories. Wind patterns may shift as temperatures rise. || **Hurricanes** | Hurricanes get energy from warm ocean water. Ocean temperature seasonality explains hurricane season. || **Closing** | You can construct an evidence-based argument about future storm changes in your region. |# Getting StartedIn the next chapter, we'll dive into our first investigative phenomenon: **Winter Storm Jonas** and the science behind blizzard formation. Get ready to think like a meteorologist! π¨οΈ